Senior Data Engineer - Remote Real-Time Pipelines

PVH (Tommy Hilfiger/Calvin Klein); United States; On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Global meet-ups

Continuous learning journey

Autonomy and flexible work environment

Supportive community

Job summary

PVH (Tommy Hilfiger/Calvin Klein) seeks a Senior Data Engineer to own and evolve data pipelines on GCP, from ingestion to transformation and ML feature layers. You will design ELT/ETL on BigQuery and ClickHouse, build streaming pipelines with Pub/Sub and Kafka, and drive data quality and reliability across the organization.

This US-remote role collaborates with ML engineers, data scientists, and analytics teams to migrate from Snowflake to a cloud-native stack and enhance observability, cost

Qualifications

• Strong data modelling and warehouse architecture skills.
• Hands-on experience with GCP data services – BigQuery is a must; Pub/Sub, Dataflow, Bigtable, Cloud Composer are strong pluses.
• Production experience with streaming pipelines on Dataflow/Beam, Flink, or Spark Structured Streaming.
• Solid SQL and strong Python – production-quality code.
• Experience with ClickHouse or another columnar OLAP engine in production.
• Workflow orchestration experience with Airflow (or Prefect/Dagster).
• Comfortable with dbt or equivalent transformation frameworks.
• Experience migrating off legacy warehouses (Snowflake, Redshift, Synapse) onto cloud-native stacks is a plus.
• Working knowledge of ML in production – feature engineering, feature stores, model deployment, drift monitoring, retraining.
• Docker & Kubernetes experience.
• CI/CD mindset, infrastructure-as-code sensibility.

Responsibilities

• Design ELT/ETL processes on BigQuery and ClickHouse, build real-time pipelines on Pub/Sub and Kafka with Dataflow (and where it fits, Flink/Spark).
• Orchestrate workflows with Airflow, ensuring data is properly cleaned, modelled, and served for analytics, ML training, and online inference.
• Partner with ML engineers on feature pipelines, monitoring data drift, and keeping models well-fed and retrained as needed.
• Consume and build REST APIs, integrate with third-party SaaS sources, and treat infrastructure as code.
• Help drive the migration off Snowflake onto the GCP-native stack and retire shadow pipelines along the way.
• Own the orchestration layer in Airflow, including SLAs, retries, and data quality gates.
• Model data for analytics and for ML – including feature pipelines that serve both training and low-latency online inference.
• Capture requirements from stakeholders and translate them into pragmatic, well-scoped data products.
• Continuously improve data quality, reliability, observability, and cost efficiency.
• Identify new data sources worthy of acquisition and integrate them cleanly.

Skills

Data modelling

Warehouse architecture

SQL

Python

Airflow

CI/CD

Infrastructure as code

Tools

BigQuery

Pub/Sub

Kafka

Dataflow (Beam)

Flink

Spark Structured Streaming

Cloud Composer

ClickHouse

dbt

Docker

Kubernetes

GitHub Actions

Datastream

Debezium

Vertex AI

Job description

PVH (Tommy Hilfiger/Calvin Klein) seeks a Senior Data Engineer to own and evolve data pipelines on GCP, from ingestion to transformation and ML feature layers. You will design ELT/ETL on BigQuery and ClickHouse, build streaming pipelines with Pub/Sub and Kafka, and drive data quality and reliability across the organization.

This US-remote role collaborates with ML engineers, data scientists, and analytics teams to migrate from Snowflake to a cloud-native stack and enhance observability, cost